Director of Analytics Engineering, Gametime

• 8+ years in analytics/data engineering roles, with at least 3+ in a technical leadership capacity
• Deep expertise in dbt, SQL, cloud data warehouses (Snowflake preferred), and modern data stack practices
• Familiarity with data visualization platforms (e.g., Sigma, Tableau, Power BI)
• A strong belief in data enablement and decentralization — paired with a disciplined approach to governance and standardization

Desirable

• Gametime is seeking a strategic and technically hands-on Director of Analytics Engineering to lead the vision, design, and implementation of a modern, AI-ready data infrastructure
• You will be responsible for establishing a robust Analytics Data Layer (ADL), enabling real-time insights, and ensuring data governance and self-service accessibility across technical, non-technical, and agentic user personas
• This role sits at the intersection of data engineering, analytics, platform strategy, and AI enablement, and will play a pivotal role in positioning Gametime to extract scalable business value from data at speed
• Collaborate with the Data Platform Team to implement an end-to-end design of a real-time, AI-ready architecture with modularity, scalability, and speed in mind
• Define and operationalize a best-in-class Analytics Data Layer (ADL) that integrates across marketing, product, finance, and customer experience datasets
• Implement a high fidelity architecture using tools like dbt, Sigma, and Snowflake to ensure high-frequency and low-latency data availability
• Own and drive the governance framework across all modeled data assets, ensuring consistency, accuracy, and security across the stack
• Codify standards for testing, documentation, and access using dbt and CI/CD pipelines to build a trusted foundation
• Architect systems that support self-service analytics across diverse personas — including analysts, operators, product managers, and AI agents
• Partner with analytics, product, and ML teams to provide structured and reusable data products
• Leverage visualization tools (e.g., Sigma, Looker, Tableau) to expose curated metrics and diagnostics via intuitive dashboards
• Lead and grow a team of analytics engineers and data modelers; act as a multiplier across the org by documenting, mentoring, and sharing best practices
• Collaborate closely with cross-functional leaders in ML Engineering, Backend, Analytics, and Finance to align data strategy with business goals